Method and system for adaptively varying templates to accommodate changes in biometric information

ABSTRACT

A method and apparatus for authenticating a user In dependence upon biometric Input information is disclosed. According to the method when a user is identified, their biometric information or data derived therefrom is automatically stored. The data is then used in subsequent user identification attempts as a template. The original templates are not replaced but those templates that are automatically stored are replaced at intervals.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of U.S. patent application Ser. No.09/797,975, which was filed on Mar. 5, 2001, now U.S. Pat. No.7,103,200.

FIELD OF THE INVENTION

The invention relates generally to biometric security systems and moreparticularly to a method of automatically updating biometric templatesbased on varying aspects of biometric information provided from a samebiometric information source.

BACKGROUND OF THE INVENTION

Computer security is fast becoming an important issue. With theproliferation of computers and computer networks into all aspects ofbusiness and daily life—financial, medical, education, government, andcommunications—the concern over secure file access is growing. Usingpasswords is a common method of providing security. Password protectionand/or combination type locks are employed for computer networksecurity, automatic teller machines, telephone banking, calling cards,telephone answering services, houses, and safes. These systems generallyrequire the knowledge of an entry code that has been selected by a useror has been preset.

Preset codes are often forgotten, as users have no reliable method ofremembering them. Writing down the codes and storing them in closeproximity to an access control device (i.e. The combination lock)results in a secure access control system with a very insecure code.Alternatively, the nuisance of trying several code variations rendersthe access control system more of a problem than a solution.

Password systems are known to suffer from other disadvantages. Usually,passwords are specified by a user. Most users, being unsophisticatedusers of security systems, choose passwords that are relativelyinsecure. As such, many password systems are easily accessed through asimple trial and error process.

A security access system that provides substantially secure access anddoes not require a password or access code is a biometric identificationsystem. A biometric identification system accepts unique biometricinformation from a user and identifies the user by matching theinformation against information belonging to registered users of thesystem. One such biometric identification system is a fingerprintrecognition system.

In a fingerprint input transducer or sensor, the finger underinvestigation is usually pressed against a flat surface, such as a sideof a glass plate; the ridge and valley pattern of the finger tip issensed by a sensing means such as an interrogating light beam.

Various optical devices are known which employ prisms upon which afinger whose print is to be identified is placed. The prism has a firstsurface upon which a finger is placed, a second surface disposed at anacute angle to the first surface through which the fingerprint is viewedand a third illumination surface through which light is directed intothe prism. In some cases, the illumination surface is at an acute angleto the first surface, as seen for example, in U.S. Pat. Nos. 5,187,482and 5,187,748. In other cases, the illumination surface is parallel tothe first surface, as seen for example, in U.S. Pat. Nos. 5,109,427 and5,233,404. Fingerprint identification devices of this nature aregenerally used to control the building-access or information-access ofindividuals to buildings, rooms, and devices such as computer terminals.

U.S. Pat. No. 4,353,056 in the name of Tsikos issued Oct. 5, 1982,discloses an alternative kind of fingerprint sensor that uses acapacitive sensing approach. The described sensor has a two dimensional,row and column, array of capacitors, each comprising a pair of spacedelectrodes, carried in a sensing member and covered by an insulatingfilm. The sensors rely upon deformation to the sensing member caused bya finger being placed thereon so as to vary locally the spacing betweencapacitor electrodes, according to the ridge/trough pattern of thefingerprint, and hence, the capacitance of the capacitors. In onearrangement, the capacitors of each column are connected in series withthe columns of capacitors connected in parallel and a voltage is appliedacross the columns. In another arrangement, a voltage is applied to eachindividual capacitor in the array. Sensing in the respective twoarrangements is accomplished by detecting the change of voltagedistribution in the series connected capacitors or by measuring thevoltage values of the individual capacitances resulting from localdeformation. To achieve this, an individual connection is required fromthe detection circuit to each capacitor.

Before the advent of computers and imaging devices, research wasconducted into fingerprint characterisation and identification. Today,much of the research focus in biometrics has been directed towardimproving the input transducer and the quality of the biometric inputdata. Fingerprint characterization is well known and can involve manyaspects of fingerprint analysis. The analysis of fingerprints isdiscussed in the following references, which are hereby incorporated byreference:

Xiao Qinghan and Bian Zhaogi,: An approach to Fingerprint IdentificationBy Using the Attributes of Feature Lines of Fingerprint,” IEEE PatternRecognition, pp 663, 1986;

C. B. Shelman, “Fingerprint Classification—Theory and Application,”Proc. 76 Carnahan Conference on Electronic Crime Countermeasures, 1976;

Feri Pernus, Stanko Kovacic, and Ludvik Gyergyek, “Minutaie BasedFingerprint Registration,” IEEE Pattern Recognition, pp 1380, 1980;

J. A. Ratkovic, F. W. Blackwell, and H. H. Bailey, “Concepts for a NextGeneration Automated Fingerprint System,” Proc. 78 Carnahan Conferenceon Electronic Crime Countermeasures, 1978;

K. Millard, “An approach to the Automatic Retrieval of LatentFingerprints,” Proc. 75 Carnahan Conference on Electronic CrimeCountermeasures, 1975;

Moayer and K. S. Fu, “A Syntactic Approach to Fingerprint PatternRecognition,” Memo Np. 73-18, Purdue University, School of ElectricalEngineering, 1973;

Wegstein, An Automated Fingerprint Identification System, NBS specialpublication, U.S. Department of Commerce/National Bureau of Standards,ISSN 0083-1883: no. 500-89, 1982;

Moenssens, Andre A., Fingerprint Techniques, Chilton Book Co., 1971;and, Wegstein and J. F. Rafferty, The LX39 Latent Fingerprint Matcher,NBS special publication, U.S. Department of Commerce/National Bureau ofStandards; no. 500-36, 1978.

In the past, user authorization based on biometric information wasconducted by correlating a single instance of biometric informationagainst a template. By using this method, a percentage of the populationis difficult to authenticate. Further, due to skin damage and injuries,sometimes biometric information is not suited to identification. A sorethroat affecting voice information and scraped fingertips affectingfingerprint information are two examples of common problems withauthorization in dependence upon biometric information.

Biometric information is commonly subject to minor variations over time.For example, as the temperature drops below freezing, the air becomesmuch more dry. With the dry weather comes drier skin. Some peopleexperience significant problems with fingerprint readers when their skinvaries with changing weather conditions. It would be advantageous toprovide a biometric identification system that automatically compensatesfor variations that result over time.

OBJECT OF THE INVENTION

It is an object of this invention to provide a method for automaticallycompensating for variations in biometric information that result overtime or are temporary in nature.

SUMMARY OF THE INVENTION

In accordance with the invention there is provided a method andapparatus for identifying a user comprising the steps of:

-   -   a) receiving a biometric information sample from the user for        use in identifying the user;    -   b) determining electronic data representing said biometric        information sample of the user;    -   c) analyzing the electronic data to compare the electronic data        against first stored data relating to identifications of users;    -   d) when a substantial match is found, identifying the        individual; and,    -   e) when a difference between the electronic data and the first        stored data is above a predetermined other threshold, comparing        the electronic data against adaptive enrollments, the adaptive        enrollments relating to biometric information samples provided        by the user for use in identifying the user by the steps (a)        through (e).

In accordance with the invention there is also provided a method andapparatus for identifying a user comprising the steps of:

-   -   a) receiving a biometric information sample from the user for        use in identifying the user;    -   b) determining electronic data representing said biometric        information sample of the user;    -   c) analyzing the electronic data to compare the electronic data        against stored data, the stored data relating to identifications        of users;    -   d) when a substantial match is found, performing the steps of:    -   identifying the individual;    -   storing the electronic data in association with the user        identification as further stored data;    -   determining from the further stored data comparison data for use        in identifying the user and different from the stored data; and,    -   e) when a difference between the electronic data and the stored        data is above a predetermined other threshold, comparing the        electronic data against other stored data, the other stored data        relating to biometric information samples provided for use in        identifying the user according to steps (a) to (e).

In accordance with the invention there is also provided a method andapparatus for identifying a user comprising the steps of:

-   -   receiving a biometric information sample from the user for use        in identifying the user;    -   determining electronic data representing said biometric        information sample of the user;    -   analyzing the electronic data to extract features for comparison        with stored electronic data;    -   comparing the extracted features against stored electronic data,        the stored electronic data relating to identifications of users;    -   when a substantial match is found, performing the steps of:    -   identifying the individual;    -   determining a number of times that the user has been identified        and when the number is one of at least a predetermined number;    -   storing the electronic data in association with the user        identification as further stored data;    -   determining from the further stored data comparison data for use        in identifying the user and different from the stored data; and,    -   when a difference between the electronic data and the stored        data is above a predetermined other threshold, comparing the        electronic data against other stored data, the other stored data        relating to biometric information samples provided for use in        identifying the user.

In accordance with the invention there is also provided a method andapparatus for identifying a user comprising the steps of:

-   -   forming at least a first template including biometric features        for use in identifying an individual;    -   forming a history file including a plurality of biometric        information samples each provided by the same individual at        different times for use in identifying the individual;    -   forming at least an adaptive enrollment template from the        biometric information samples in the history file,    -   wherein an individual is identified by registering provided        biometric information sample against the at least a first        template and, when registration is not successful registering        the provided biometric information sample against the at least        an adaptive enrollment template.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a simplified flow diagram of a process for biometricenrollment, according to the prior art;

FIG. 2 shows a simplified flow diagram of an adaptive biometricenrollment method, according to the present invention;

FIG. 3 shows a simplified flow diagram of a method for recognizing auser in dependence upon a biometric input, according to the presentinvention; and,

FIG. 4 shows a simplified flow diagram of a method for comparingbiometric information against three adaptive enrollments updated in acircular fashion, according to the present invention.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

The invention is described with respect to finger print registration.The method of this invention is applicable to other biometricverification processes as is evident to those of skill in the art.

There are two common architectures for use with biometric identificationsystems, one-to-one and one-to-many. In one-to-one biometricidentification, a user is identified separate from the biometricidentification process and the identification is verified by verifyingbiometric data provided with a template associated with the identifiedindividual. Such a system, because only one instance of sensed biometricinformation is compared against one template, is relatively secure. Thatsaid, the architecture is not well suited to some applications. In aone-to-many architecture, a single fingerprint is compared againstnumerous templates to isolate a template that most closely matchesbiometric information provided. The security of the system is oftenlower than that of a system employing a one-to-one architecture but aone-to-many architecture allows for user identification with no inputdata other than the biometric information sample.

One of the problems with a finger print biometric is that a segment ofthe population can have temporary skin conditions which cause poor imagequality on the scanning device or changes in fingerprint qualities whichin turn causes them to experience high false rejection rates. One methodof overcoming this problem is to allow the use of any fingertip.Unfortunately, such a method results in a large database of templatesand, thereby results in greatly reduced overall security for one-to manyfingerprint identification systems.

Referring to FIG. 1, a flow diagram of a prior art embodiment forbiometric identification is shown. Biometric templates are stored via astatic designated biometric enrollment process. This process isconsciously executed each time a user desires to update an individualbiometric template, and involves presenting the specified biometricinformation sample to a sensor when in execution of a custom enrollmentdialog. Since the user consciously executes this enrollment process,additional expertise is implied. Alternatively, the process is executedperiodically by security personnel implying a need for additionalresources.

The motivation for executing this process at regular intervals is thatany particular biometric information sample, being linked to aconstantly changing organic signature, typically evolves with thepassage of time. In some instances, this leads to a significant increasein the false rejection rate over the span of a few months. The falserejection rate is the ratio of rejections in the form of failedcomparisons to acceptances in the form of accurate comparisons for avalid biometric information sample. This results in reduced usability,significant additional administrative overhead, and frustration.

In order to improve the biometric enrollment process the presentembodiment provides a method that enables ongoing adaptive enrollment ofbiometric information samples during normal daily operation of abiometric identification system. The adaptive enrollment process istransparent to the user and requires minimal administrative overhead.The false rejection rate is maintained at an approximately constantlevel, improving the usability of the system over prior art systems.Notification is provided to administrators as individual biometricinformation samples begin to vary in a divergent fashion from theoriginally registered biometric information samples, allowingadministrators to schedule static reenrollment of biometric informationsamples in a controlled manner as necessary.

Referring to FIG. 2, a simplified flow diagram of an embodiment of anadaptive biometric enrollment method is shown. A user provides biometricinformation to a contact imaging device. The biometric information isimaged and a digital representation of the biometric information isformed. The digital representation is then analysed to determinefeatures forming a part thereof. These features are then compared totemplates of features relating to known individuals. When a featurematch occurs within predetermined limits, the user is identified as therelated known individual.

Of course, it is well known that biometric information varies over time.For example, if a hand is soaked in water for a length of time, thefingerprint changes. Similarly, when the weather is extremely dry afingerprint changes a bit. Further, different imaging devices rely ondifferent phenomena. Some imagers require some moisture to effectivelyimage but cannot tolerate too much moisture. Of course, as seasonschange, moisture levels in the air vary and so do moisture levels withinpeoples' skin.

When features within a digital representation match those of a template,a distance between the digital representation and the template iscalculated. This distance is used to determine whether the digitalrepresentation should be stored as a subsidiary template. Adaptiveenrollments in the form of subsidiary templates are useful to allow forcompensation for variations in biometric information that occur overtime. For example, as the weather gets colder, the fingertips grow driercausing effective changes in the imaged fingerprint. By storing newadaptive enrollments in the form of subsidiary templates when a user isidentified, the system is provided with templates that more closelymatch a current biometric information sample of the user.

In FIG. 2, the digital representation is outside a predetermineddistance from the template and as such is stored as an adaptiveenrollment. The digital representation is also compared to determine adistance from the originally enrolled template. When the distance isbeyond a predetermined maximum distance, security is notified tore-enroll the user to establish a new base template. This preventstemplates from drifting too far from the originally enrolled template.Of course, as shown in FIG. 2, the adaptive enrollment is a firstadaptive enrollment for the user and as such the distance from theoriginally enrolled template is within the predetermined limits.

Referring to FIG. 3, a flow diagram of a method of recognizing a user isshown. A user provides biometric information to a contact imagingdevice. The biometric information is imaged and a digital representationof the biometric information is formed. The digital representation isthen analyzed to determine features forming a part thereof. Thesefeatures are then compared to templates of features relating to knownindividuals. When a feature match occurs within predetermined limits,the user is identified as the related known individual.

In the flow diagram of FIG. 3, none of the original templates match thefeatures within predetermined limits. The closest template is thenselected and the features are compared against adaptive enrollmentsrelating to that template. Alternatively, several closest templates areselected. When a match is determined within the predetermined limits orwithin other predetermined limits depending on design parameters, theuser is identified. Thus there is no performance impact during anauthentication that compares successfully against a statically enrolledbiometric and the performance impact for failed registrations is verysmall. The recognition of individuals who would heretofore have beenfalsely rejected is advantageously achieved.

In a preferred embodiment, an authentication server database memorydiagram for which is shown in FIG. 4, three classes of biometrictemplate enrollments are stored in the authentication server database. Amaster enrollment, generated from a statically enrolled biometricinformation source, is stored for each biometric. The maser enrollmentsare updated during a static enrollment process. A number of historicalenrollments are stored for each biometric template based on data withina configuration file. The historical enrollments are updated in acircular fashion by replacing an oldest historical enrollment with a newhistorical enrollment. A new historical enrollment is generatedperiodically based on a configuration file defined period. Threeadaptive enrollments, composed of the three historical enrollments withthe highest composite comparison metric, are stored for each biometric.The adaptive enrollments are updated each time a new historicalenrollment is stored. Additional processing required for processingadaptive enrollments typically executes in a background thread on theauthentication server.

For example, an adaptive enrollment occurs the first time a userattempts to authenticate biometrically after a span of time greater thanthe adaptive enrollment period has passed since the last adaptiveenrollment. The following procedures is followed:

The provided biometric data in the form of a digital representation iscompared against each template in the set of master enrollmenttemplates. If a match is found then authentication occurs and thedigital representation is queued for processing by a background thread.If a match is not found then the closest matching template from themaster enrollment templates is used to determine which biometric waspresented and a master enrollment match failure is logged. The digitalrepresentation is compared against each template in the set of adaptiveenrollments for that biometric. In the example of FIG. 4 that is threetemplates. If a match is found then authentication occurs and theauthentication biometric is queued for processing by the backgroundthread. If a match is not found then authentication fails and thedigital representation is discarded.

The background thread executes periodically and examines the queue forany digital representations that are newly added. If the queue is emptythen the background thread terminates until it is executed again after atime period. If the queue is not empty then each digital representationis processed in turn to form the three adaptive enrollments.

When there exist a predetermined number of historical enrollmentsassociated with a template the oldest digital representation isdetermined and is compared against all he other historical enrollmentsin the set in order to calculate a set of comparison metrics. Thecomposite comparison metric for each historical enrollment associatedwith the template is updated by subtracting the relevant comparisonmetric. The oldest digital representation is deleted.

When there exist fewer than the predetermined number of historicalenrollments associated with a template then the digital representationis compared against all the historical enrollments associated with themaster enrollment template in order to calculate a set of comparisonmetrics. The composite comparison metric for each historical enrollmentassociated with the template is updated by adding the relevantcomparison metric. The digital representation is stored as a newhistorical enrollment and its composite comparison metric is calculatedfrom the average of the individual comparison metrics for all the otherhistorical enrollments associated with the master template and themaster enrollment template.

The three historical enrollments with the largest composite comparisonmetrics associated with a template are designated the adaptiveenrollments associated with the template. These enrollments are copiedand restored in order to optimize their retrieval and comparison duringthe authentication process. Alternatively, they are not copied and theirretrieval and comparison requires additional time.

In order to describe the adaptive enrollment process, it is helpful toprovide a concise mathematical characterization of a preferred compositecomparison metric, as well as the subtraction and addition operations.

The composite comparison metric for historical enrollment i is given by

${m_{i} = \frac{\sum\limits_{\underset{j \neq i}{{j = 1},}}^{n}{c\left( {H_{i},H_{j}} \right)}}{n - 1}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}}$where n is the number of historical enrollments in the set andc(H_(i),H_(j)) is the comparison metric between biometric template i andbiometric template j.

The updated composite comparison metric for historical enrollment iafter the subtraction operation on historical enrollment j is given by

${m_{i} = {m_{i} - \frac{c\left( {H_{i},H_{j}} \right)}{n - 1}}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}},{i \neq j}$where n is the number of historical enrollments in the set includinghistorical enrollment j.

The updated composite comparison metric for historical enrollment iafter the addition operation on historical enrollment j is given by

${m_{i} = {m_{i} + \frac{c\left( {H_{i},H_{j}} \right)}{n - 1}}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}},{i \neq j}$where n is the number of historical enrollments in the set includinghistorical enrollment j.

Of course, it is also possible to provide a new historic enrollment witheach successful identification. Unfortunately, it is generally foundthat such a system results in a history that is either too cumbersome toprocess or unlikely to be of sufficient duration to track many slowlyvarying changes in biometric information. Preferably, historicenrollments are captured one or two times during a week period.

When the adaptive enrollments are more than a predetermined distancefrom the master enrollment templates, security is notified to re-enrollthe individual. This prevents slow drifting biometric information fromoverlapping with another user, thereby resulting in false acceptances.

Preferably, more than one master enrollment is used. Using, for example,three master enrollment templates allows for more effective useridentification. Alternatively, using more than one master enrollmenttemplate allows for selection of diverse templates that are accurate fora particular user as master templates in order to provide enhanced spacewithin which to successfully identify a user.

Though the above method is described with reference to backgroundprocessing and to minimizing performance impact caused by the method,other implementations of the invention are equally possible.

Numerous other embodiments of the invention may be envisaged withoutdeparting from the spirit or scope of the invention.

1. A system for identifying a user comprising: an authentication serverthat stores templates relating to identifications of users; and aprocessing device programmed to: determine electronic data representinga biometric information sample from a biometric source of the user;analyze the electronic data to compare the electronic data againststored biometric templates relating to identifications of users; when afirst threshold corresponding to a substantial match of a template issatisfied, identify the individual; and when a difference between theelectronic data and the matched template is above a predetermined secondthreshold, store a new biometric template in said authentication serveras an adaptive enrollment for the user based on the electronic datarelating to biometric information samples for said biometric source asprovided by the user for use in identifying the user.
 2. A systemaccording to claim 1 wherein for every predetermined number ofoccurrences of a substantial match, the processing device: stores theelectronic data within a history file; analyzes the electronic data todetermine its suitability for use as the adaptive enrollment; and whenthe electronic data is determined to be suitable, stores the electronicdata as the adaptive enrollment.
 3. A system according to claim 2wherein the history file comprises up to N samples of electronic dataand wherein an oldest sample of electronic data is deleted by theprocessing device when a new sample of electronic data is added to ahistory file containing N samples.
 4. A system according to claim 3wherein a score is stored in association with each sample electronicdata within the history file indicating a suitability of the sample foruse as the adaptive enrollment.
 5. A system according to claim 4 whereinthe score is determined by the processing device by comparing the sampleelectronic data against each other sample electronic data within thehistory file and associated with a same user identification.
 6. A systemaccording to claim 5 wherein the score is determined by the processingdevice by determining a composite comparison metric, M_(i) for eachsample electronic data, i,${m_{i} = \frac{\sum\limits_{\underset{j \neq i}{{j = 1},}}^{n}{c\left( {H_{i},H_{j}} \right)}}{n - 1}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}}$where n is the number of historical enrollments in the set andc(H_(i),H_(j)) is the comparison metric between biometric template i andbiometric template j.
 7. A system according to claim 5 wherein upondeleting a sample electronic data from the history file, its effect onthe scores in the history file is approximately reversed.
 8. A systemaccording to claim 7 wherein the effect is approximately reversed bysaid processing device by recalculating m, after the deletion of sampleelectronic element j according to${m_{i} = {m_{i} - \frac{c\left( {H_{i},H_{j}} \right)}{n - 1}}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}},{i \neq j}$where n is the number of historical enrollments in the set includinghistorical enrollment j.
 9. A system according to claim 8 wherein theeffect of an added sample electronic element j is determined by theprocessing device by calculating m_(i) according to${m_{i} = {m_{i} + \frac{c\left( {H_{i},H_{j}} \right)}{n - 1}}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}},{i \neq j}$where n is the number of historical enrollments in the set includinghistorical enrollment j.
 10. A system according to claim 2 wherein theeffect of an added sample electronic element j is determined by theprocessing device by calculating m_(i) according to${m_{i} = {m_{i} + \frac{c\left( {H_{i},H_{j}} \right)}{n - 1}}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}},{i \neq j}$where n is the number of historical enrollments in the set includinghistorical enrollment j.
 11. A system according to claim 2 whereinelectronic data samples suitable for use as the adaptive enrollment arecompared against the stored data by the processing device, and when adifference greater than a predetermined difference exists, anotification of such is generated.
 12. A system according to claim 2wherein electronic data samples are compared against the stored data bythe processing device, and when a difference greater than apredetermined difference exists, the user is prompted to re-enroll inorder to provide new biometric information for use in determining newstored data.
 13. A system for identifying a user comprising: anauthentication server that stores templates relating to identificationsof users; and a processing device programmed to: receive a biometricinformation sample from a biometric source of the user for use inidentifying the user; determine electronic data representing saidbiometric information sample of the user; analyze the electronic data tocompare the electronic data against stored biometric template datarelating to identifications of users; when a first thresholdcorresponding to a substantial match of a template is satisfied:identify the individual; store the electronic data in association withthe user identification as further stored biometric template data; anddetermine from the further stored biometric template data comparisondata for use in identifying the user; and when a difference between theelectronic data and the stored biometric template data is above apredetermined second threshold, compare the electronic data againstother stored biometric template data relating to biometric informationsamples for said biometric source as provided for use in identifying theuser.
 14. A system according to claim 13 wherein the further storedbiometric template data relates to different features of the individual,the features for use in identifying the individual.
 15. A systemaccording to claim 13 wherein the processing device stores theelectronic data in association with the user identification as furtherstored biometric template data by storing an electronic representationof the biometric information sample associated with the identification.16. A system according to claim 15 wherein the processing devicedetermines from the further stored biometric template data comparisondata for use in identifying the user by: comparing each storedelectronic representation associated with the identification against atemplate derived from each other electronic representation associatedwith the identification to select at least an electronic representationthat best represents the stored electronic representations associatedwith the identification; and determining at least a template from the atleast a selected electronic representation.
 17. A system according toclaim 15 wherein the processing device determines from the furtherstored biometric template data comparison data for use in identifyingthe user by: storing with each electronic representation associated withthe identification a score indicative of a quality of the storedelectronic representations associated with the identification for use ingenerating a template; comparing the oldest stored electronicrepresentation associated with the identification against a templatederived from each other electronic representation associated with theidentification to determine the conection for the score associated withsaid template; correcting each score in accordance with the determinedcorrections; comparing the newest stored electronic representationassociated with the identification against a template derived from eachother electronic representation associated with the identification todetermine a second conection for each score; correcting each score inaccordance with the determined second correction; and selecting anelectronic representation associated with a best score for use indetermining a template for use as the comparison data.
 18. A system foridentifying a user comprising: means for receiving a biometricinformation sample from a biometric source of the user for use inidentifying the user; means for determining electronic data representingsaid biometric information sample of the user; means for analyzing theelectronic data to extract features for comparison with storedelectronic data; means for comparing the extracted features againststored electronic data, the stored electronic data relating toidentifications of users; means for, when a substantial match is found:identifying the individual; determining a number of times that the userhas been identified and when the number is one of at least apredetermined number; storing the electronic data in association withthe user identification as further stored data; and determining from thefurther stored data comparison data for use in identifying the user;and, means for, when a difference between the electronic data and thestored data is above a predetermined threshold, comparing the electronicdata against other stored data, the other stored data relating toadditional biometric information samples for said biometric source asprovided for use in identifying the user.
 19. A system for identifying auser comprising: an authentication server that stores templates relatingto identifications of users; and a processing device programmed to:receive a biometric information sample from a biometric source of theuser; form from said biometric information sample at least a firsttemplate including biometric features for use in identifying anindividual; form a history file including a plurality of biometricinformation samples from said biometric source each provided by the sameindividual at different times for use in identifying the individual; andform at least one adaptive enrollment template from the biometricinformation samples from said biometric source in the history file,wherein an individual is identified by registering provided biometricinformation sample against the at least a first template and, whenregistration is not successful, registering the provided biometricinformation sample against the at least one adaptive enrollmenttemplate.
 20. A system according to claim 19 wherein the at least oneadaptive enrollment template is a template formed from one or morebiometric information samples within the history file, the one or morebiometric information samples selected through a comparison with otherbiometric information samples within the history file.
 21. A systemaccording to claim 20 wherein each biometric information sample storedwithin the history file is compared against each other biometricinformation sample within the history file by the processing device todetermine those that are most suitable for use in determining adaptiveenrollment templates.
 22. A system according to claim 21 wherein thehistory file comprises up to N biometric information samples and whereinan oldest biometric information sample is deleted by the processingdevice when a new biometric information sample is added to a historyfile containing N samples.
 23. A system according to claim 22 wherein ascore is stored in association with each biometric information samplewithin the history file indicating a suitability of that sample for usein determining an adaptive enrollment template.
 24. A system accordingto claim 23 wherein the score is determined by the processing device bycomparing the sample electronic data against each other sampleelectronic data within the history file and associated with a same useridentification.
 25. A system according to claim 24 wherein the score isdetermined by the processing device by determining a compositecomparison metric, M_(i) for each sample electronic data, i,${m_{i} = \frac{\sum\limits_{\underset{j \neq i}{{j = 1},}}^{n}{c\left( {H_{i},H_{j}} \right)}}{n - 1}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}}$where n is the number of historical enrollments in the set andc(H_(i),H_(j)) is the comparison metric between biometric template i andbiometric template j.
 26. A system according to claim 24 wherein upondeleting a sample electronic data from the history file, its effect onthe scores in the history file is approximately reversed.
 27. A systemaccording to claim 26 wherein the effect is approximately reversed bythe processing device by recalculating m_(i) after the deletion ofsample electronic element j according to${m_{i} = {m_{i} - \frac{c\left( {H_{i},H_{j}} \right)}{n - 1}}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}},{i \neq j}$where n is the number of historical enrollments in the set includinghistorical enrollment j.
 28. A system according to claim 27 wherein theeffect of an added sample electronic element j is determined by theprocessing device by calculating m_(i) according to${m_{i} = {m_{i} + \frac{c\left( {H_{i},H_{j}} \right)}{n - 1}}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}},{1 \neq j}$wherein n is the number of historical enrollments in the set includinghistorical enrollment j.
 29. A system according to claim 19 wherein theeffect of an added sample electronic element j is determined by theprocessing device by calculating m_(i) according to${m_{i} = {m_{i} + \frac{c\left( {H_{i},H_{j}} \right)}{n - 1}}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}},{i \neq j}$where n is the number of historical enrollments in the set includinghistorical enrollment j.
 30. A system according to claim 19 whereinadaptive enrollment templates are compared against the at least a firsttemplate by the processing device and, when a difference greater than apredetermined difference exists, a notification of such is generated.31. A system according to claim 19 wherein adaptive enrollment templatesare compared against the at least a first template by the processingdevice and, when a difference greater than a predetermined differenceexists, the user is prompted to re-enroll in order to provide newbiometric information for use in determining a new at least a firsttemplate.
 32. A computer readable medium having executable instructionsstored thereon that when read by a computer causes the computer to:receive a biometric information sample from a biometric source of a userfor use in identifying the user; determine electronic data representingsaid biometric information sample of the user; analyze the electronicdata to compare the electronic data against biometric templates relatingto identifications of users; when a first threshold corresponding to asubstantial match of a template is satisfied, identify the individual;and, when a difference between the electronic data and the matchedtemplate is above a predetermined second threshold, store a newbiometric template as an adaptive enrollment for the user based on theelectronic data relating to biometric information samples for saidbiometric source as provided by the user for use in identifying theuser.
 33. A computer readable medium according to claim 32 furtherhaving stored thereon executable instructions that for everypredetermined number of occurrences of a substantial match, causes thecomputer to: store the electronic data within a history file; analyzethe electronic data to determine its suitability for use as the adaptiveenrollment; and when the electronic data is determined to be suitable,store the electronic data as the adaptive enrollment.
 34. A computerreadable medium according to claim 33 wherein the history file comprisesup to N samples of electronic data and wherein the computer readablemedium further comprises executable instructions for causing thecomputer to delete an oldest sample of electronic data when a new sampleof electronic data is added to a history file containing N samples. 35.A computer readable medium according to claim 34 further comprisingexecutable instructions for causing the computer to store a score inassociation with each sample electronic data within the history fileindicating a suitability of the sample for use as the adaptiveenrollment.
 36. A computer readable medium according to claim 35 furthercomprising executable instructions for causing the computer to determinethe score by comparing the sample electronic data against each othersample electronic data within the history file and associated with asame user identification.
 37. A computer readable medium according toclaim 36 further comprising executable instructions for causing thecomputer to determine the score by determining a composite comparisonmetric, M_(i) for each sample electronic data, i,${m_{i} = \frac{\sum\limits_{\underset{{j \neq i}\;}{{j = 1},}}^{n}{c\left( {H_{i},H_{j}} \right)}}{n - 1}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}}$where n is the number of historical enrollments in the set and c(H_(i),H_(j)) is the comparison metric between biometric template i andbiometric template j.
 38. A computer readable medium according to claim36 further comprising executable instructions for causing the computerto, upon deleting a sample electronic data from the history file,approximately reverse the effect of the sample electronic data on thescores in the history file.
 39. A computer readable medium according toclaim 38 further comprising executable instructions for causing thecomputer to approximately reverse the effect of the sample electronicdata by recalculating m, after the deletion of sample electronic elementj according to${m_{i} = {m_{i} - \frac{c\left( {H_{i},H_{j}} \right)}{n - 1}}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}},{i \neq j}$where n is the number of historical enrollments in the set includinghistorical enrollment j.
 40. A computer readable medium according toclaim 39 further comprising executable instructions for causing thecomputer to determine the effect of an added sample electronic element jby calculating m_(i) according to${m_{i} = {m_{i} + \frac{c\left( {H_{i},H_{j}} \right)}{n - 1}}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}},{i \neq j}$where n is the number of historical enrollments in the set includinghistorical enrollment j.
 41. A computer readable medium according toclaim 33 further comprising executable instructions for causing thecomputer to determine the effect of an added sample electronic element jby calculating m_(i) according to${m_{i} = {m_{i} + \frac{c\left( {H_{i},H_{j}} \right)}{n - 1}}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}},{i \neq j}$where n is the number of historical enrollments in the set includinghistorical enrollment j.
 42. A computer readable medium according toclaim 33 further comprising executable instructions for causing thecomputer to compare electronic data samples suitable for use as theadaptive enrollment against the stored data, and when a differencegreater than a predetermined difference exists, generate a notificationof such.
 43. A computer readable medium according to claim 33 furthercomprising executable instructions for causing the computer to compareelectronic data samples against the stored data, and when a differencegreater than a predetermined difference exists, prompt the user tore-enroll in order to provide new biometric information for use indetermining new stored data.
 44. A computer readable medium havingexecutable instructions stored thereon that when read by a computercauses the computer to identify a user by: receiving a biometricinformation sample from a biometric source of the user for use inidentifying the user; determining electronic data representing saidbiometric information sample of the user; analyzing the electronic datato compare the electronic data against stored biometric template datarelating to identifications of users; when a first thresholdcorresponding to a substantial match of a template is satisfied:identifying the individual; storing the electronic data in associationwith the user identification as further stored biometric template data;determining from the further stored biometric template data comparisondata for use in identifying the user; and e) when a difference betweenthe electronic data and the stored biometric template data is above apredetermined second threshold, comparing the electronic data againstother stored biometric template data relating to biometric informationsamples for said biometric source as provided for use in identifying theuser.
 45. A computer readable medium according to claim 44 wherein thefurther stored biometric template data relates to different features ofthe individual, the features for use in identifying the individual. 46.A computer readable medium according to claim 44 wherein storing theelectronic data in association with the user identification as furtherstored biometric template data comprises storing an electronicrepresentation of the biometric information sample associated with theidentification.
 47. A computer readable medium according to claim 46wherein determining from the further stored biometric template datacomparison data for use in identifying the user includes: comparing eachstored electronic representation associated with the identificationagainst a template derived from each other electronic representationassociated with the identification to select at least an electronicrepresentation that best represents the stored electronicrepresentations associated with the identification; and determining atleast a template from the at least a selected electronic representation.48. A computer readable medium according to claim 46 wherein determiningfrom the further stored biometric template data comparison data for usein identifying the user includes: storing with each electronicrepresentation associated with the identification a score indicative ofa quality of the stored electronic representations associated with theidentification for use in generating a template; comparing the oldeststored electronic representation associated with the identificationagainst a template derived from each other electronic representationassociated with the identification to determine the correction for thescore associated with said template; correcting each score in accordancewith the determined corrections; comparing the newest stored electronicrepresentation associated with the identification against a templatederived from each other electronic representation associated with theidentification to determine a second correction for each score;correcting each score in accordance with the determined secondcorrection; and selecting an electronic representation associated with abest score for use in determining a template for use as the comparisondata.
 49. A computer readable medium having executable instructionsstored thereon that when read by a computer causes the computer toidentify a user by: receiving a biometric information sample from abiometric source of the user for use in identifying the user;determining electronic data representing said biometric informationsample of the user; analyzing the electronic data to extract featuresfor comparison with stored electronic data; comparing the extractedfeatures against stored electronic data, the stored electronic datarelating to identifications of users; and when a substantial match isfound: identifying the individual; determining a number of times thatthe user has been identified and when the number is one of at least apredetermined number; storing the electronic data in association withthe user identification as further stored data; and determining from thefurther stored data comparison data for use in identifying the user; andwhen a difference between the electronic data and the stored data isabove a predetermined threshold, comparing the electronic data againstother stored data, the other stored data relating to additionalbiometric information samples for said biometric source as provided foruse in identifying the user.
 50. A computer readable medium havingexecutable instructions stored thereon that when read by a computercauses the computer to identify a user by: receiving a biometricinformation sample from a biometric source of the user; forming fromsaid biometric information sample at least a first template includingbiometric features for use in identifying an individual; forming ahistory file including a plurality of biometric information samples fromsaid biometric source each provided by the same individual at differenttimes for use in identifying the individual; and forming at least oneadaptive enrollment template from the biometric information samples fromsaid biometric source in the history file, wherein an individual isidentified by registering provided biometric information sample againstthe at least a first template and, when registration is not successful,registering the provided biometric information sample against the atleast one adaptive enrollment template.
 51. A computer readable mediumaccording to claim 50 wherein the at least one adaptive enrollmenttemplate is a template formed from one or more biometric informationsamples within the history file, the one or more biometric informationsamples selected through a comparison with other biometric informationsamples within the history file.
 52. A computer readable mediumaccording to claim 51 further comprising executable instructions forcomparing each biometric information sample stored within the historyfile against each other biometric information sample within the historyfile to determine those that are most suitable for use in determiningadaptive enrollment templates.
 53. A computer readable medium accordingto claim 52 wherein the history file comprises up to N biometricinformation samples further comprising executable instructions fordeleting an oldest biometric information sample when a new biometricinformation sample is added to a history file containing N samples. 54.A computer readable medium according to claim 53 further comprisingexecutable instructions for storing a score in association with eachbiometric information sample within the history file indicating asuitability of that sample for use in determining an adaptive enrollmenttemplate.
 55. A computer readable medium according to claim 54 furthercomprising executable instructions for determining the score bycomparing the sample electronic data against each other sampleelectronic data within the history file and associated with a same useridentification.
 56. A computer readable medium according to claim 55further comprising executable instructions for determining the score bydetermining a composite comparison metric, M_(i) for each sampleelectronic data, i,${m_{i} = \frac{\sum\limits_{\underset{{j \neq i}\;}{{j = 1},}}^{n}{c\left( {H_{i},H_{j}} \right)}}{n - 1}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}}$where n is the number of historical enrollments in the set andc(H_(i),H_(j)) is the comparison metric between biometric template i andbiometric template j.
 57. A computer readable medium according to claim55 further comprising executable instructions for, upon deleting asample electronic data from the history file, approximately reversingthe effect of said sample electronic data on the scores in the historyfile.
 58. A computer readable medium according to claim 57 furthercomprising executable instructions for approximately reversing theeffect of the sample electronic data on the scores in the history fileby recalculating m_(i) after the deletion of sample electronic element jaccording to${m_{i} = {m_{i} - \frac{c\left( {H_{i},H_{j}} \right)}{n - 1}}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}},{i \neq j}$where n is the number of historical enrollments in the set includinghistorical enrollment j.
 59. A computer readable medium according toclaim 58 further comprising executable instructions for determining theeffect of an added sample electronic element j by calculating m_(i)according to${m_{i} = {m_{i} + \frac{c\left( {H_{i},H_{j}} \right)}{n - 1}}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}},{i \neq j}$wherein n is the number of historical enrollments in the set includinghistorical enrollment j.
 60. A computer readable medium according toclaim 50 further comprising executable instructions for determining theeffect of an added sample electronic element j by calculating m_(i)according to${m_{i} = {m_{i} + \frac{c\left( {H_{i},H_{j}} \right)}{n - 1}}},{i \in \left\{ {1,\ldots\mspace{11mu},n} \right\}},{i \neq j}$where n is the number of historical enrollments in the set includinghistorical enrollment j.
 61. A computer readable medium according toclaim 50 further comprising executable instructions for comparingadaptive enrollment templates against the at least a first template and,when a difference greater than a predetermined difference exists,generating a notification of such.
 62. A computer readable mediumaccording to claim 50 further comprising executable instructions forcomparing adaptive enrollment templates against the at least a firsttemplate and, when a difference greater than a predetermined differenceexists, prompting the user to re-enroll in order to provide newbiometric information for use in determining a new at least a firsttemplate.